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Comparison of peripheral and central schizophrenia biomarker profiles.

ABSTRACT: We have recently shown that a molecular biomarker signature comprised of inflammatory, hormonal and growth factors occurs in the blood serum from first onset schizophrenia patients. Here, we use the same platform to investigate post mortem brain tissue (Brodmann area 10) from schizophrenia patients who were mainly chronically ill and drug treated. Twenty-one analytes are differentially expressed in post-mortem brain tissue. Comparison with our previous mRNA profiling studies of the same patient samples in another frontal cortical area showed that 9 of these molecules were also altered at the transcriptional level. Furthermore, 9 of the molecules were also altered in serum from living first onset schizophrenia patients compared to controls. We propose a model in which the brain and periphery are coordinated through hormones and other regulatory molecules released into the blood via the diffuse neuroendocrine system. These findings provide further evidence for the systemic nature of schizophrenia and give added validity to the concept that schizophrenia can be investigated through studies of blood-based biomarkers.

SUBMITTER: Harris LW

PROVIDER: S-EPMC3484150 | biostudies-literature | 2012

REPOSITORIES: biostudies-literature

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Comparison of peripheral and central schizophrenia biomarker profiles.

Harris Laura W LW Pietsch Sandra S Cheng Tammy M K TM Schwarz Emanuel E Guest Paul C PC Bahn Sabine S

PloS one 20121030 10

We have recently shown that a molecular biomarker signature comprised of inflammatory, hormonal and growth factors occurs in the blood serum from first onset schizophrenia patients. Here, we use the same platform to investigate post mortem brain tissue (Brodmann area 10) from schizophrenia patients who were mainly chronically ill and drug treated. Twenty-one analytes are differentially expressed in post-mortem brain tissue. Comparison with our previous mRNA profiling studies of the same patient ...[more]

PMID: 23118852

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Project description:The incidence of Alzheimer's disease (AD) increases with age and is becoming a significant cause of worldwide morbidity and mortality. However, the metabolic perturbation behind the onset of AD remains unclear. In this study, we performed metabolite profiling in both brain (n?=?109) and matching serum samples (n?=?566) to identify differentially expressed metabolites and metabolic pathways associated with neuropathology and cognitive performance and to identify individuals at high risk of developing cognitive impairment. The abundances of 6 metabolites, glycolithocholate (GLCA), petroselinic acid, linoleic acid, myristic acid, palmitic acid, palmitoleic acid and the deoxycholate/cholate (DCA/CA) ratio, along with the dysregulation scores of 3 metabolic pathways, primary bile acid biosynthesis, fatty acid biosynthesis, and biosynthesis of unsaturated fatty acids showed significant differences across both brain and serum diagnostic groups (P-value?<?0.05). Significant associations were observed between the levels of differential metabolites/pathways and cognitive performance, neurofibrillary tangles, and neuritic plaque burden. Metabolites abundances and personalized metabolic pathways scores were used to derive machine learning models, respectively, that could be used to differentiate cognitively impaired persons from those without cognitive impairment (median area under the receiver operating characteristic curve (AUC)?=?0.772 for the metabolite level model; median AUC?=?0.731 for the pathway level model). Utilizing these two models on the entire baseline control group, we identified those who experienced cognitive decline in the later years (AUC?=?0.804, sensitivity?=?0.722, specificity?=?0.749 for the metabolite level model; AUC?=?0.778, sensitivity?=?0.633, specificity?=?0.825 for the pathway level model) and demonstrated their pre-AD onset prediction potentials. Our study provides a proof-of-concept that it is possible to discriminate antecedent cognitive impairment in older adults before the onset of overt clinical symptoms using metabolomics. Our findings, if validated in future studies, could enable the earlier detection and intervention of cognitive impairment that may halt its progression.

Dataset Information

Comparison of peripheral and central schizophrenia biomarker profiles.

Publications

Comparison of peripheral and central schizophrenia biomarker profiles.

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